Project Objective
This is a personal project on a subject that has stirred and continues to stir a lot of debate on social media. The data for this project was scraped from Twitter by running a query of the keyword “climate change”. The project comprises analyses of sentiments and emotions found in tweets about climate change, and analyses of the keywords as well.
Sentiment and Emotion Analyses
A total of 18000 tweets were analyzed for the sentiments and emotions expressed in them.
Text Analyses
Here, I analyze and visualize the most frequently occurring words in the tweets about climate change.
Bi-grams and Co-occurrences
Next, I analyze the tweets for the most relevant bi-grams, using the rapid automatic keywords extraction algorithm (RAKE).
Finally, I create a dendrogram to visualize co-occurring words in the tweets. That is, words that occur within the same context.
The sentiment and emotion analyses show that climate change is still a subject that worries people, because more human and development activities continue to threaten the global environment. Also, the bi-grams and co-occurring words reveal the different aspects of climate change that people want addressed.